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Python 大数据思维导图

2013-06-14 12:47 1171 查看




Python for big data
1 Basic stack
1.1 numpy
1.2 scipy
1.3 pandas
1.3.1 "Python for Data Analysis" by Wes McKinney
1.4 scikits image
1.5 scikits learn
1.6 scikits statsmodels
1.7 nltk
1.8 matplotlib
2 Newer packages
2.1 Numba
2.2 wiseRF
2.3 Blaze
3 Integrated platforms
3.1 Continuum.io
3.1.1 Anaconda
3.1.2 Wakari
3.2 PiCloud
3.2.1 Python + AWS
3.3 wise.io
3.3.1 MLaaS
3.3.1.1 RandomForest
3.4 ipython
3.4.1 Notebook
3.5 Orange
4 Visualization
4.1 matplotlib
4.2 Bokeh
4.2.1 ggplot for python
4.3 Mayavi
4.4 Nodebox
4.5 igraph
4.6 pandas
4.6.1 pandas.tools.rplot
4.7 Google APIs
4.7.1 googleVis
5 Data formats
5.1 Flat text
5.1.1 xreadlines
5.1.2 readLines
5.1.3 pandas
5.1.3.1 read_csv
5.1.3.2 read_fwf
5.1.4 xlrd/xlwt/xlutils
5.2 HDF5
5.2.1 PyTables
5.2.2 h5py
5.3 SQL
5.3.1 SQLAlchemy
5.3.2 pysqlite3
5.3.3 pyodbc
5.3.3.1 Vertica
5.3.3.2 Netezza
5.3.3.3 Teradata
5.4 NoSQL
5.4.1 MongoDB
5.4.1.1 PyMongo
5.4.2 CouchDB
5.4.2.1 couchdb-python
5.4.2.2 couchdbkit
5.5 JSON
5.5.1 Standard library
5.5.1.1 json
5.5.2 simplejson
5.6 XML
5.6.1 Standard library
5.6.1.1 xml
5.7 HBase
5.7.1 HappyBase
6 MapReduce
6.1 Hadoop interface
6.1.1 Hadoop Streaming
6.1.1.1 Hadoopy
6.1.1.2 example
6.1.1.3 dumbo
6.1.1.4 mrjob Used and developed by Yelp
6.1.2 Pydoop
6.1.2.1 uses Hadoop Pipes
6.2 disco Used and developed by Nokia
7 Glue
7.1 rpy2
7.1.1 R
7.2 PySpark
7.2.1 Spark
7.3 ipython
7.3.1 magic
7.3.1.1 R
7.3.1.2 SQL
7.3.1.3 matlab/octave
7.3.1.4 IDL
7.4 Jython
7.4.1 Java
7.5 boto
7.5.1 Amazon Web Services
8 GPU
8.1 NumbaPro
8.2 PyCUDA
9 Parallel
9.1 ipython
9.1.1 ipcluster
9.2 pp
9.3 dispy
10 Efficiency
10.1 Cython
11 Packages
11.1 PyPI
11.1.1 30686 packages
VIA:
Python for big data

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